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2008

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Improving image segmentation by gradient vector flow and mean shift

14 years 11 days ago

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The classical gradient vector flow (GVF) method suffers from deficiency in the presence of other significant edges adjacent to the real boundary. In this paper, we propose an impr...

Tangwei Liu, Huiyu Zhou, Faquan Lin, Yusheng Pang,...

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Id	Views	Title	Status

1	356	Improving image segmentation by gradient vector flow and mean shift	claim
2	270	Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers	claim
3	253	RotBoost: A technique for combining Rotation Forest and AdaBoost	claim
4	246	Automatic medical image annotation in ImageCLEF 2007: Overview, results, and discussion	claim
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7	198	Pose estimation and tracking using multivariate regression	claim
8	181	Extractive spoken document summarization for information retrieval	claim
9	161	Automatic kernel clustering with a Multi-Elitist Particle Swarm Optimization Algorithm	claim
10	152	WND-CHARM: Multi-purpose image classification using compound image transforms	claim
11	147	Deformations, patches, and discriminative models for automatic annotation of medical radiographs	claim
12	143	An active feedback framework for image retrieval	claim
13	142	Highly accurate error-driven method for noun phrase detection	claim
14	137	On-line handwritten digit recognition based on trajectory and velocity modeling	claim
15	135	A hierarchical clustering algorithm based on the Hungarian method	claim
16	133	Better multiclass classification via a margin-optimized single binary problem	claim
17	132	Confidence based multiple classifier fusion in speaker verification	claim
18	131	Progressive structural analysis for dynamic recognition of on-line handwritten mathematical expressions	claim
19	126	Fourier-based geometric shape prior for snakes	claim
20	124	Matrix-pattern-oriented least squares support vector classifier with AdaBoost	claim
21	124	Modeling human color categorization	claim
22	124	Constructing cylindrical coordinate colour spaces	claim
23	122	Constraints for closest point finding	claim
24	118	A large margin approach for writer independent online handwriting classification	claim
25	118	Bayes Machines for binary classification	claim
26	113	A new normalized method on line-based homography estimation	claim
27	111	On applying linear discriminant analysis for multi-labeled problems	claim
28	108	Discriminative cue integration for medical image annotation	claim
29	103	A study on the relevance criteria for medical images	claim
30	102	The 1.5D sieve algorithm	claim
31	101	Illumination-robust face recognition using ridge regressive bilinear models	claim
32	98	Cross-validation and bootstrapping are unreliable in small sample classification	claim
33	97	Repairing self-confident active-transductive learners using systematic exploration	claim
34	96	Outlier rejection for cameras on intelligent vehicles	claim
35	95	Semi-supervised learning by search of optimal target vector	claim
36	93	Learning to learn: From smart machines to intelligent machines	claim
37	91	Fuzzy relevance vector machine for learning from unbalanced data and noise	claim
38	91	Approximating non-metrical Minkowski distances in 2D	claim
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40	88	Time-efficient spam e-mail filtering using n-gram models	claim
41	85	Reliability estimation of a statistical classifier	claim
42	84	Classification of packed executables for accurate computer virus detection	claim
43	83	A theoretical comparison of two-class Fisher's and heteroscedastic linear dimensionality reduction schemes	claim
44	82	Optimistic pruning for multiple instance learning	claim
45	81	Selecting and constructing features using grammatical evolution	claim
46	81	Learning automata based classifier	claim
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48	79	Efficient least squares fusion of MRI and CT images using a phase congruency model	claim
49	79	Can graph-cutting improve microarray gene expression reconstructions?	claim
50	78	A framework and baseline results for the CLEF medical automatic annotation task	claim
51	78	Retrieving scale from quasi-stationary images	claim
52	78	Pattern recognition in interdisciplinary perception and intelligence	claim
53	75	The peaking phenomenon in the presence of feature-selection	claim
54	74	Pose determination and plane measurement using a trapezium	claim
55	68	Text-independent speaker recognition using graph matching	claim
56	67	A Gaussian kernel-based fuzzy c-means algorithm with a spatial bias correction	claim
57	66	Multi-dimensional visual tracking using scatter search particle filter	claim
58	66	Nucleus and cytoplast contour detector of cervical smear image	claim
59	65	Matching of quasi-periodic time series patterns by exchange of block-sorting signatures	claim
60	58	A non-local regularization strategy for image deconvolution	claim
61	54	On lexicographical ordering in multivariate mathematical morphology	claim
62	53	Selecting features for object detection using an AdaBoost-compatible evaluation function	claim

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